mgcvUI
An Interactive Interface for the mgcv (Generalized Additive Models) Package
DOI:
https://doi.org/10.67330/xtv1pa25Keywords:
mgcv(), Generalized Additive Models, mgcvUI(), regression for real estateAbstract
mgcvUI is a graphical user interface for the R mgcv package, which fits Generalized Additive Models (GAMs) using penalized regression splines with automatic smoothness selection.
It offers three purpose modes—general predictive modeling, real-estate appraisal, and market-area analysis—and guides the user through data import, smooth-term specification, model fitting, diagnostic and effect plots, and downloadable reports. This article documents mgcvUI’s data-format requirements, modeling workflow, output displays, and complete feature reference.
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References
Wood, S. N. 2003. “Thin-Plate Regression Splines.” Journal of the Royal Statistical Society (B) 65 (1): 95–114. https://doi.org/10.1111/1467-9868.00374.
Wood, S. N. 2004. “Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models.” Journal of the American Statistical Association 99 (467): 673–86. https://doi.org/10.1198/016214504000000980.
Wood, S. N. 2011. “Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models.” Journal of the Royal Statistical Society (B) 73 (1): 3–36. https://doi.org/10.1111/j.1467-9868.2010.00749.x.
Wood, S. N. 2017. Generalized Additive Models: An Introduction with R. 2nd ed. Chapman; Hall/CRC.
Wood, S. N., N. Pya, and B. Säfken. 2016. “Smoothing Parameter and Model Selection for General Smooth Models (with Discussion).” Journal of the American Statistical Association 111: 1548–75. https://doi.org/10.1080/01621459.2016.1180986.
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